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Josep Llados; Felipe Lumbreras; V. Chapaprieta; J. Queralt |
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Title |
ICAR: Identity Card Automatic Reader. |
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Miscellaneous |
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2001 |
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Sixth International Conference on Document Analysis and Recognition |
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ICDAR 2001 |
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470–474 |
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USA |
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ADAS @ adas @ LLC2001 |
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112 |
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Author |
Josep Llados; Felipe Lumbreras; Javier Varona |
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Title |
A multidocument platform for automatic reading of identity cards. |
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Miscellaneous |
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1999 |
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Proceedings of the VIII Symposium Nacional de Reconocimiento de Formas y Analisis de Imagenes. |
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Bilbao |
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ADAS @ adas @ LLV1999 |
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7 |
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Author |
Antonio Lopez; Ernest Valveny; Juan J. Villanueva |
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Title |
Real-time quality control of surgical material packaging by artificial vision |
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2005 |
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Assembly Automation |
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25 |
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3 |
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IF: 0.061) |
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ADAS;DAG |
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ADAS @ adas @ LVV2005 |
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552 |
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Author |
Ernest Valveny; Antonio Lopez |
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Title |
Numeral Recognition for Quality Control of Surgical Sachets |
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2003 |
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Proceedings of the Seventh International Conference on Document Analysis and Recognition (ICDAR´03), 379–383 |
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ADAS @ adas @ VaL2003 |
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423 |
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Author |
Maria Vanrell; Felipe Lumbreras; A. Pujol; Ramon Baldrich; Josep Llados; Juan J. Villanueva |
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Title |
Colour Normalisation Based on Background Information. |
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Miscellaneous |
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2001 |
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Proceeding ICIP 2001, IEEE International Conference on Image Processing |
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ICIP 2001 |
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1 |
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874–877 |
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Grecia. |
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ADAS;DAG;CIC |
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ADAS @ adas @ VLP2001 |
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167 |
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Author |
Marçal Rusiñol; V. Poulain d'Andecy; Dimosthenis Karatzas; Josep Llados |
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Title |
Classification of Administrative Document Images by Logo Identification |
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Conference Article |
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2013 |
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10th IAPR International Workshop on Graphics Recognition |
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This paper is focused on the categorization of administrative document images (such as invoices) based on the recognition of the supplier's graphical logo. Two different methods are proposed, the first one uses a bag-of-visual-words model whereas the second one tries to locate logo images described by the blurred shape model descriptor within documents by a sliding-window technique. Preliminar results are reported with a dataset of real administrative documents. |
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Bethlehem; PA; USA; August 2013 |
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GREC |
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DAG; 600.056; 600.045; 605.203 |
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Admin @ si @ |
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2348 |
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Author |
Pau Riba; Alicia Fornes; Josep Llados |
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Title |
Towards the Alignment of Handwritten Music Scores |
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2015 |
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11th IAPR International Workshop on Graphics Recognition |
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It is very common to find different versions of the same music work in archives of Opera Theaters. These differences correspond to modifications and annotations from the musicians. From the musicologist point of view, these variations are very interesting and deserve study. This paper explores the alignment of music scores as a tool for automatically detecting the passages that contain such differences. Given the difficulties in the recognition of handwritten music scores, our goal is to align the music scores and at the same time, avoid the recognition of music elements as much as possible. After removing the staff lines, braces and ties, the bar lines are detected. Then, the bar units are described as a whole using the Blurred Shape Model. The bar units alignment is performed by using Dynamic Time Warping. The analysis of the alignment path is used to detect the variations in the music scores. The method has been evaluated on a subset of the CVC-MUSCIMA dataset, showing encouraging results. |
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Nancy; France; August 2015 |
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Springer International Publishing |
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Bart Lamiroy; Rafael Dueire Lins |
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978-3-319-52158-9 |
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GREC |
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DAG |
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Admin @ si @ |
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2874 |
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Author |
Marçal Rusiñol; Dimosthenis Karatzas; Josep Llados |
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Title |
Automatic Verification of Properly Signed Multi-page Document Images |
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Conference Article |
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2015 |
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Proceedings of the Eleventh International Symposium on Visual Computing |
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9475 |
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327-336 |
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Document Image; Manual Inspection; Signature Verification; Rejection Criterion; Document Flow |
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In this paper we present an industrial application for the automatic screening of incoming multi-page documents in a banking workflow aimed at determining whether these documents are properly signed or not. The proposed method is divided in three main steps. First individual pages are classified in order to identify the pages that should contain a signature. In a second step, we segment within those key pages the location where the signatures should appear. The last step checks whether the signatures are present or not. Our method is tested in a real large-scale environment and we report the results when checking two different types of real multi-page contracts, having in total more than 14,500 pages. |
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Las Vegas, Nevada, USA; December 2015 |
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9475 |
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ISVC |
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DAG; 600.077 |
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Admin @ si @ |
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3189 |
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Author |
L. Rothacker; Marçal Rusiñol; Josep Llados; G.A. Fink |
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Title |
A Two-stage Approach to Segmentation-Free Query-by-example Word Spotting |
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2014 |
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Manuscript Cultures |
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7 |
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47-58 |
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With the ongoing progress in digitization, huge document collections and archives have become available to a broad audience. Scanned document images can be transmitted electronically and studied simultaneously throughout the world. While this is very beneficial, it is often impossible to perform automated searches on these document collections. Optical character recognition usually fails when it comes to handwritten or historic documents. In order to address the need for exploring document collections rapidly, researchers are working on word spotting. In query-by-example word spotting scenarios, the user selects an exemplary occurrence of the query word in a document image. The word spotting system then retrieves all regions in the collection that are visually similar to the given example of the query word. The best matching regions are presented to the user and no actual transcription is required.
An important property of a word spotting system is the computational speed with which queries can be executed. In our previous work, we presented a relatively slow but high-precision method. In the present work, we will extend this baseline system to an integrated two-stage approach. In a coarse-grained first stage, we will filter document images efficiently in order to identify regions that are likely to contain the query word. In the fine-grained second stage, these regions will be analyzed with our previously presented high-precision method. Finally, we will report recognition results and query times for the well-known George Washington
benchmark in our evaluation. We achieve state-of-the-art recognition results while the query times can be reduced to 50% in comparison with our baseline. |
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DAG; 600.061; 600.077 |
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Admin @ si @ |
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3190 |
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Author |
Josep Llados; Daniel Lopresti; Seiichi Uchida (eds) |
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Title |
16th International Conference, 2021, Proceedings, Part III |
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2021 |
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Document Analysis and Recognition – ICDAR 2021 |
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12823 |
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This four-volume set of LNCS 12821, LNCS 12822, LNCS 12823 and LNCS 12824, constitutes the refereed proceedings of the 16th International Conference on Document Analysis and Recognition, ICDAR 2021, held in Lausanne, Switzerland in September 2021. The 182 full papers were carefully reviewed and selected from 340 submissions, and are presented with 13 competition reports.
The papers are organized into the following topical sections: document analysis for literature search, document summarization and translation, multimedia document analysis, mobile text recognition, document analysis for social good, indexing and retrieval of documents, physical and logical layout analysis, recognition of tables and formulas, and natural language processing (NLP) for document understanding. |
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Lausanne, Switzerland, September 5-10, 2021 |
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Springer Cham |
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Josep Llados; Daniel Lopresti; Seiichi Uchida |
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978-3-030-86333-3 |
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ICDAR |
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Admin @ si @ |
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3727 |
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